Attenuated Induction of the Unfolded Protein Response in Adult Human Primary Astrocytes in Response to Recurrent Low Glucose

Abstract

Aims/hypothesisRecurrent hypoglycaemia (RH) is a major side-effect of intensive insulin therapy for people with diabetes. Changes in hypoglycaemia sensing by the brain contribute to the development of impaired counterregulatory responses to and awareness of hypoglycaemia. Little is known about the intrinsic changes in human astrocytes in response to acute and recurrent low glucose (RLG) exposure.MethodsHuman primary astrocytes (HPA) were exposed to zero, one, three or four bouts of low glucose (0.1 mmol/l) for three hours per day for four days to mimic RH. On the fourth day, DNA and RNA were collected. Differential gene expression and ontology analyses were performed using DESeq2 and GOseq, respectively. DNA methylation was assessed using the Infinium MethylationEPIC BeadChip platform.Results24 differentially expressed genes (DEGs) were detected (after correction for multiple comparisons). One bout of low glucose exposure had the largest effect on gene expression. Pathway analyses revealed that endoplasmic-reticulum (ER) stress-related genes such as HSPA5, XBP1, and MANF, involved in the unfolded protein response (UPR), were all significantly increased following low glucose (LG) exposure, which was diminished following RLG. There was little correlation between differentially methylated positions and changes in gene expression yet the number of bouts of LG exposure produced distinct methylation signatures.Conclusions/interpretationThese data suggest that exposure of human astrocytes to transient LG triggers activation of genes involved in the UPR linked to endoplasmic reticulum (ER) stress. Following RLG, the activation of UPR related genes was diminished, suggesting attenuated ER stress. This may be a consequence of a successful metabolic adaptation, as previously reported, that better preserves intracellular energy levels and a reduced necessity for the UPR.

Hierarchical deconvolution for extensive cell type resolution in the human brain using DNA methylation

“…We used five publicly available data sets containing DNA methylation data on purified brain cells to construct our brain deconvolution libraries ( Table 1 ). The discovery data sets included isolated samples from human primary astrocytes from the post-mortem sub-ventricular deep white matter ( Weightman Potter et al, 2021 ; n = 6), endothelial cells from the cord tissue ( Lin et al, 2018 ; n = 12), GABAergic neurons (GABA; Kozlenkov et al, 2018 ; n = 5) and glutamatergic neurons (GLU; Kozlenkov et al, 2018 ; n = 5) from the post-mortem dorsolateral prefrontal cortex, microglial cells from the post-mortem medial frontal gyrus, superior temporal gyrus, subventricular zone and thalamus ( de Witte et al, 2022 ; n = 18), oligodendrocytes from the post-mortem Brodmann area 46 ( Mendizabal et al, 2019 ; n = 20), and stromal cells from the cord tissue ( Lin et al, 2018 ; n = 14). Due to the lack of age and sex information for astrocytes, Horvath methylation age and inferred sex were calculated using ENMIX ( Xu et al, 2016 ) and SeSAMe ( Zhou et al, 2018 ), respectively.…”